Author

Cheng Chen

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#artificial intelligence Preprint Sep 2026

From Language to Behavior: Scaling Sequence Transformers for Industrial Recommendation Ranking with Rec-Native Designs

ReST is proposed, a recommendation-native Transformer scaling framework that achieves higher accuracy and scales more consistently along sequence length, depth, and width, where LLM-style Transformer blocks saturate.

Jie Chen, Xiang-Qia Yu, Yan-Chao Lian et al. · 0 citations

Jul 2026

LaRec: Unleashing LLM-based Latent Reasoning for Generative Recommendation

This work proposes LaRec, an efficient generative recommendation framework designed to unleash the potential of latent reasoning in LLMs by designing Latent Pre-training that empowers LLMs with latent reasoning capabilities by providing rich supervisory signals to the latent space reasoning via step-level alignment and...

Yu Xia, Zihan Lin, Wei Yang et al. · arXiv.org · 0 citations